Hydrogeological map of Lower Saxony 1: 50000 – Change of mean annual groundwater regeneration for the 30-year period 2021-2050 to 1971-2000 in the hydrological summer half-year No climate protection scenario (RCP8.5)

The map shows the modeled change in mean annual groundwater formation for the 30-year period 2071-2100 to 1971-2000 in the hydrological summer half-year (May-Oct.) in mm/a calculated with the “no-climate protection” scenario (RCP8.5). Groundwater is a raw material that can regenerate and renew itself. The main supplier of groundwater supplies is rainwater leaking in Lower Saxony. It ensures that the groundwater deposits of the storage rocks are replenished in the underground. The new groundwater formation is particularly high in winter, as at this time a large part of the rainfall is leaking in the soil. In the warmer seasons, however, a large part of the precipitation evaporates on the surface or is absorbed by plants. The formation of groundwater is widely distributed in different areas. It depends on the distribution of precipitation and evaporation, the characteristics of the soil, the land use (growth, degree of sealing), the relief of the land surface, the artificial drainage by drainage, the groundwater level and the properties of the near-surface rocks. Since these parameters differ significantly in Lower Saxony, in some cases in the smallest space, the formation of groundwater is also subject to large lateral fluctuations. In order to determine the new formation of groundwater, there are various methods. The present maps show the area-differentiated designation of the mean groundwater formation, which was calculated using the mGROWA method (short for “monthly large-scale water balance”). The model mGROWA was developed for the large-scale simulation of the water balance at Forschungszentrum Jülich in cooperation with the LBEG (Herrmann et al. 2013) and since 2016 for Lower Saxony updated methodologically. In addition, a number of new input data was used to provide an up-to-date data base for water management planning work and water licensing procedures. Daily and monthly climate projection data were used as climatic input data. The climate projection data represent the results of an ensemble of different climate models (the Lower Saxony climate ensemble AR5-NI v2.1 see Hajati et al. (2022)). The data was provided by the German Weather Service. The data is based on the EURO-CORDEX Ensemble (Jacob et al., 2014). Within the framework of the BMVI expert network, the DWD scaled down from a 12.5 km to a 5 km grid. The climate models are powered by the “No Climate Protection” scenario (RCP8.5). This is a scenario of the IPCC, which describes a continuous increase in global greenhouse gas emissions, which by the end of the 21st century generates an additional radiative forcing of 8.5 watts per m² compared to pre-industrial levels. The results of all climate models are equally likely. Therefore, in addition to the mean that shows a tendency, the upper (maximum) and lower (minimum) edges of the result bandwidth can be retrieved via the MapTip. For better regionalisation, the climatic input parameters of precipitation and potential evaporation with bilinear interpolation were scaled down to a 500 x 500 m grid for mGROWA22.本地图展示了基于"无气候保护"情景（RCP8.5）计算得到的水文夏季半年（5月至10月）多年平均地下水补给量（groundwater formation）变化，时段为2071-2100年与1971-2000年的对比，单位为毫米每年（mm/a）。 地下水是一种可循环再生的自然资源。下萨克森州（Lower Saxony）的地下水补给主要来源于入渗雨水：雨水通过下渗补充地下储水岩层中的地下水储量。冬季的地下水补给量尤为充沛，此时大部分降雨会渗入土壤；而在暖季，多数降水会在地表蒸发或被植物吸收。 地下水补给量的空间分布极广，其影响因素包括降水与蒸发的空间分布、土壤特性、土地利用方式（植被覆盖度、地表硬化程度）、地表地形、人工排水措施、地下水位以及近地表岩层性质。由于下萨克森州内上述参数差异显著，部分区域甚至在极小空间范围内即存在显著差异，因此地下水补给量也存在较大的横向波动。 地下水补给量的测算方法多种多样。本系列地图展示了分区的多年平均地下水补给量结果，该结果基于mGROWA方法（monthly large-scale water balance，即月度大尺度水量平衡）计算得到。mGROWA模型由于利希研究中心（Forschungszentrum Jülich）与LBEG合作开发，用于大尺度水量平衡模拟（Herrmann等，2013）；自2016年起，该模型针对下萨克森州完成了方法学更新。此外，本次研究还采用了多组新的输入数据，以期为水资源管理规划与取水许可审批工作提供最新的数据库支撑。 本研究采用逐日及逐月气候预估数据作为气候输入参数。该气候预估数据源自多气候模式集合模拟结果（下萨克森州气候集合AR5-NI v2.1，详见Hajati等，2022），由德国气象局（German Weather Service, DWD）提供。数据基于EURO-CORDEX集合（EURO-CORDEX Ensemble）模拟结果（Jacob等，2014）。在BMVI专家网络框架下，德国气象局将原始数据从12.5km分辨率降尺度至5km分辨率。 本次模拟采用的气候模式基于"无气候保护"情景（RCP8.5）。该情景为政府间气候变化专门委员会（IPCC）所提出的一种全球温室气体排放持续增长的情景，至21世纪末，其相较于工业化前水平的额外辐射强迫（radiative forcing）可达8.5瓦每平方米（W/m²）。 所有气候模式的模拟结果权重均等。因此，除了体现变化趋势的平均值之外，用户还可通过地图提示（MapTip）获取结果区间的上限（最大值）与下限（最小值）。 为实现更精准的区域化处理，针对mGROWA22模型，研究人员采用双线性插值（bilinear interpolation）法将降水与潜在蒸发量（potential evaporation）的气候输入参数降尺度至500×500米的网格分辨率。